High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing

Zhang, Peng; Xia, Ji‐Han; Zhu, Jing; Gao, Ping; Tian, Yi; Du, Meijun; Guo, Yuanbo; Suleman, Sufyan; Zhang, Qin; Kohli, Manish; Tillmans, Lori S.; Thibodeau, Stephen N.; French, Amy J.; Cerhan, James R.; Wang, Li Dong; Wei, Gong-Hong; Wang, Liang

doi:10.1038/s41467-018-04451-x

Cited by 73 publications

(84 citation statements)

References 53 publications

(57 reference statements)

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“…For all eQTL signals in the linkage equilibrium block, the association of rs13426236 with MLPH expression was among the most significant ( P = 8.49E−09; Figure A). The SNP rs13426236, which demonstrated allele‐dependent protein binding difference, was selected from our previous study …”

Section: Resultsmentioning

confidence: 99%

“…Previous GWAS has identified a significant association of 2q37.3 locus with increased risk to prostate cancer . Further eQTL analysis has revealed MLPH as one candidate gene since SNPs at this locus are associated with the gene expression in prostate tissues . In this study, we performed detail functional analysis of the SNP‐gene association, elucidated the genetic control of MLPH expression and determined the functional role of the gene in cell growth and migration.…”

Section: Discussionmentioning

confidence: 96%

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Single‐nucleotide polymorphism rs13426236 contributes to an increased prostate cancer risk via regulating MLPH splicing variant 4

Xiao

Zhang

Wang

et al. 2019

Molecular Carcinogenesis

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A prostate cancer risk single-nucleotide polymorphism (SNP), rs13426236, is significantly associated with melanophilin (MLPH) expression. To functionally characterize role of the rs13426236 in prostate cancer, we first performed splicing-specific expression quantitative trait loci analysis and refined the significant association of rs13426236 allele G with an increased expression of MLPH splicing transcript variant 4 (V4) (P = 7.61E−5) but not other protein-coding variants (V1-V3) (P > .05). We then performed an allele-specific reporter assay to determine if SNP-containing sequences functioned as an active enhancer.Compared to allele A, allele G of rs13426236 showed significantly higher luciferase activity on the promoter of the splicing transcript V4 (P < .03) but not on the promoter of transcript V1 (P > .05) in two prostate cancer cell lines (DU145 and 22Rv1). Cell transfection assays showed stronger effect of transcript V4 than V1 on promoting cell proliferation, invasion, and antiapoptotic activities. RNA profiling analysis demonstrated that transcript V4 overexpression caused significant expression changes in glycosylation/ glycoprotein and metal-binding gene ontology pathways (FDR < 0.01). We also found that both transcripts V4 and V1 were significantly upregulated in prostate adenocarcinoma (P ≤ 2.49E−6) but only transcript V4 upregulation was associated with poor recurrencefree survival (P = .028, hazard ratio = 1.63, 95% confidence interval = 1.05-2.42) in The Cancer Genome Atlas data. This study provides strong evidence showing that prostate cancer risk SNP rs13426236 upregulates expression of MLPH transcript V4, which may function as a candidate oncogene in prostate cancer.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 96%

Single‐nucleotide polymorphism rs13426236 contributes to an increased prostate cancer risk via regulating MLPH splicing variant 4

Xiao

Zhang

Wang

et al. 2019

Molecular Carcinogenesis

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“…MPRAs have previously been used successfully to generate initial lists of SNPs that can alter the activity of regulatory elements [20][21][22][23][24] . These earlier efforts, however, covered only a tiny proportion of the total collection of human SNPs.…”

Section: Discussionmentioning

confidence: 99%

“…Large-scale versions of this approach are referred to as Massively Parallel Reporter Assays (MPRAs). So far, MPRAs have been successfully applied to screen tens of thousands of SNPs [20][21][22][23][24] . Each of these studies has yielded tens to at most several hundreds of SNPs that significantly alter promoter or enhancer activity.…”

Section: Introductionmentioning

confidence: 99%

Systematic identification of human SNPs affecting regulatory element activity

Arensbergen

Pagie

FitzPatrick

et al. 2018

Preprint

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Most of the millions of single-nucleotide polymorphisms (SNPs) in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on enhancer and promoter activity. Here, we have leveraged the throughput of the SuRE reporter technology to survey a total of 5.9 million SNPs, including 57% of the known common SNPs. We identified more than 30 thousand SNPs that alter the activity of putative regulatory elements, often in a cell-type specific manner. These data indicate that a large proportion of human non-coding SNPs may affect gene regulation. Integration of these SuRE data with genome-wide association studies may help pinpoint SNPs that underlie human traits.

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“…Yet, on average these methods rarely accomplish single-SNP resolution, and even less, complete analysis of all credible SNPs. Alternatively, massively parallel reporter assays (MPRAs) present scalable, functional readouts to genetic variation: DNA sequence elements from each allele are inserted into a reporter plasmid and once transfected into cells, the promoter or enhancer activity of these elements is measured quantitatively [84][85][86][87][88]. As of yet, MPRA studies have covered only a tiny fraction of the genome.…”

Section: Cataloging Credible Risk Snps and Genesmentioning

confidence: 99%

Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders

Hoffmann

Ziller

Spengler

2020

Cells

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Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.

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High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing

Cited by 73 publications

References 53 publications

Single‐nucleotide polymorphism rs13426236 contributes to an increased prostate cancer risk via regulating MLPH splicing variant 4

Single‐nucleotide polymorphism rs13426236 contributes to an increased prostate cancer risk via regulating MLPH splicing variant 4

Systematic identification of human SNPs affecting regulatory element activity

Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders

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